Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting
As a key enabler of the access traffic steering, switching and splitting (ATSSS) feature, multipath transport can leverage the simultaneous use of several network paths and support seamless failover to improve both communication throughput and resilience. Therefore, a traffic scheduling strategy is...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/9/3285 |
| _version_ | 1827671420173287424 |
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| author | Xinran Ba Libiao Jin Zengrui Li Jianhe Du Sidong Li |
| author_facet | Xinran Ba Libiao Jin Zengrui Li Jianhe Du Sidong Li |
| author_sort | Xinran Ba |
| collection | DOAJ |
| description | As a key enabler of the access traffic steering, switching and splitting (ATSSS) feature, multipath transport can leverage the simultaneous use of several network paths and support seamless failover to improve both communication throughput and resilience. Therefore, a traffic scheduling strategy is necessary to determine the best network path combination that may improve the performance of multipath transport. To address this need, we developed a multiservice-type based transmission (MSTT) traffic scheduling optimization strategy, which involves three steps. First, the user equipment (UE) selects the number of data stream transmission paths, considering the service utility function, and either transmits all data streams via the 3GPP network or sends two streams, one via the 3GPP network and the other via the non-3GPP network. Second, the proposed method is used to select the transmission path for each data stream based on load balancing. Finally, an algorithm for optimizing traffic scheduling is formulated by applying the convex optimization problem to maximize the effective network capacity under a Delay Quality of Service (DQoS) constraint. The proposed traffic scheduling strategy is validated through simulation experiments. The results indicate that user satisfaction and effective capacity realized are always better than when using the always-best-connected and fixed-ratio power-allocation algorithms. |
| first_indexed | 2024-03-10T03:41:41Z |
| format | Article |
| id | doaj.art-1a91a4359fba4029be28bbadb8ee9943 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:41:41Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1a91a4359fba4029be28bbadb8ee99432023-11-23T09:16:11ZengMDPI AGSensors1424-82202022-04-01229328510.3390/s22093285Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and SplittingXinran Ba0Libiao Jin1Zengrui Li2Jianhe Du3Sidong Li4State Key Laboratory of Media Convergence and Communication, School of Information and Communication Engineering, Communication University of China, Beijing 100024, ChinaSchool of Information and Communication Engineering, Communication University of China, Beijing 100024, ChinaSchool of Information and Communication Engineering, Communication University of China, Beijing 100024, ChinaSchool of Information and Communication Engineering, Communication University of China, Beijing 100024, ChinaDatang Mobile Communication Equipment Co., Ltd., Beijing 100083, ChinaAs a key enabler of the access traffic steering, switching and splitting (ATSSS) feature, multipath transport can leverage the simultaneous use of several network paths and support seamless failover to improve both communication throughput and resilience. Therefore, a traffic scheduling strategy is necessary to determine the best network path combination that may improve the performance of multipath transport. To address this need, we developed a multiservice-type based transmission (MSTT) traffic scheduling optimization strategy, which involves three steps. First, the user equipment (UE) selects the number of data stream transmission paths, considering the service utility function, and either transmits all data streams via the 3GPP network or sends two streams, one via the 3GPP network and the other via the non-3GPP network. Second, the proposed method is used to select the transmission path for each data stream based on load balancing. Finally, an algorithm for optimizing traffic scheduling is formulated by applying the convex optimization problem to maximize the effective network capacity under a Delay Quality of Service (DQoS) constraint. The proposed traffic scheduling strategy is validated through simulation experiments. The results indicate that user satisfaction and effective capacity realized are always better than when using the always-best-connected and fixed-ratio power-allocation algorithms.https://www.mdpi.com/1424-8220/22/9/3285ATSSSmultipath transportmultiserviceeffective network capacity |
| spellingShingle | Xinran Ba Libiao Jin Zengrui Li Jianhe Du Sidong Li Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting Sensors ATSSS multipath transport multiservice effective network capacity |
| title | Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting |
| title_full | Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting |
| title_fullStr | Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting |
| title_full_unstemmed | Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting |
| title_short | Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting |
| title_sort | multiservice based traffic scheduling for 5g access traffic steering switching and splitting |
| topic | ATSSS multipath transport multiservice effective network capacity |
| url | https://www.mdpi.com/1424-8220/22/9/3285 |
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